International Journal of Environmental Engineering and Development
Print ISSN: , E-ISSN: 2945-1159
Volume 1, 2023
Machine Learning Enabled Crop Recommendation System for Arid Land
Authors: Batool Alsowaiq, Noura Almusaynid, Esra Albhnasawi, Wadha Alfenais, Suresh Sankaranarayanan
Abstract: The agriculture industry plays a significant role in the economy of many countries, and the population is regarded as an essential profession. To increase agricultural production, crops are recommended based on soil, weather, humidity, rainfall, and other variables which are beneficial to farmers as well as the nation. This paper explores the use of “machine learning” algorithms to recommend crops in for Arid land based on features selected from tropical climate where crops grow effectively. Five “machine learning” models have been validated for recommendation of crops for arid land which resulted in “Random Forest” topping as the best model.
Search Articles
Keywords: Crop recommendation, Machine Learning, Random Forest. Humidity, rainfall
Pages: 56-61
DOI: 10.37394/232033.2023.1.7
International Journal of Environmental Engineering and Development, ISSN / E-ISSN: / 2945-1159, Volume 1, 2023, Art. #7